International Journal of Network Security & Its Applications (IJNSA) - ERA, WJCI Indexed

International Journal of Network Security & Its Applications (IJNSA) - ERA, WJCI Indexed

ISSN: 0974 - 9330 (Online); 0975 - 2307 (Print)

Webpage URL: https://airccse.org/journal/ijnsa.html

Cyberguard: Fake Profile Detection using Machine Learning

M.Vijaya Lakshmi, Aishwarya Rao, Kalyani Boddulah, Ojaswi Cheekati and Varsha Vadla, G. Narayanamma Institute of Technology and Science (For Women), India

Abstract

Social media platforms that foster high levels of user engagement, such as Facebook, Instagram, and Twitter, have huge impact on people's lives everywhere. They still have issues with false profiles, which may be created by automated systems, computer programs, or individuals. These false accounts facilitate illicit activities like phishing and identity theft as well as the dissemination of rumors. To solve this issue, our study employs many machine learning techniques to differentiate between authentic and fraudulent Twitter profiles. Analysis is done using key data including the quantity of friends and followers, activity trends, and more.

The algorithms such as Random Forest, XG Boost, LSTM, and neural networks emphasizes how crucial itis to choose important criteria while evaluating social media accounts. After training, the models generatea value of 1 for bogus profiles and 0 for real ones, allowing for the identification and the removal of bogus profiles to lessen cybersecurity risks.

Keywords

Random forest, LSTM, XG Boost, Twitter, social media, fake profiles, machine learning, and neural networks

Abstract URL: http://aircconline.com/abstract/ijnsa/v16n3/16324ijnsa04.html

Original Source URL: https://aircconline.com/ijnsa/V16N3/16324ijnsa04.pdf

Volume URL: https://airccse.org/journal/jnsa24_current.html